Jose Serva

P DSL Cubs Blue

Age 18 LHP ROK peak 0.2 · 2028

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	17	ROKDSL Cubs Blue	11	11	31	2.64	2.64	29.0%	12.1%	—	K 19.7% · BB 15.1% · FIP 3.97
2027PROJ	18	MLBCHC	3	3	18	4.93	4.93	22.2%	13.5%	-0.0
2028PROJ49% MLB	19	MLBCHC	3	3	14	4.75	4.67	22.7%	12.0%	0.0

Next 2 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0 WAR median (P10 0 / P90 0, comp-based) · star 0% · didn't stick 96%

CompsJagger Haynes (age 20) · Julio Mendez (age 17) · Ethan Lindow (age 18)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 111119vR 127

ERA4.93

FIP4.93

K%22.2%

BB%13.5%

K-BB%8.7%

Proj IP18

Value2027 · WAR

Runs saved vs league avg · 18 IP

Grades · Contract

Scouting Grades

K†5555

Contract

No contract data on file. Pre-MLB players and minor-league free agents do not yet have salary projections — entries are added at first 40-man roster placement.

Career Stats + Projections

Real MLB stats plus park-adjusted projections — this season (so far / rest / full), then future seasons and career totals.

show model inputsbasis chips: RAW = as recorded · CTX = with park/league context · A+C = actual + context combined · MLE = level/park-neutral

Methodology▸ how WAR & MLE are computed

Stats are park-neutral MLB equivalents. The "TEAM" column shows current org affiliation only — we do NOT project at that team's park.
Rates (K%, BB%, HR-BF) are park-stripped; MiLB stat lines are translated to their MLB-equivalent via per-level MLE factors.
WAR is computed from projected runs prevented vs a replacement pitcher (the marginal arm a team would call up if this pitcher were unavailable) — calibrated to industry-standard fWAR.

Year	Age	Lvl	Team	G	GS	IP	BF	K	BB	HR	GS%	IP/G	K%	BB%	K-BB%	HR%	ERA	FIP	WAR
▸ Career — actual stats, one row per year (as recorded, no adjustments)
▸ Career — adjusted (each season translated to a park/league-neutral MLB-equivalent line; levels combined per year)
▸ Model inputs — neutral MLE (past 3 seasons + 2027 so far)
2026	17	ROK MLE	DSL Cubs Blue	11	11	31	124	36	15	1	100%	2.8	19.7%	15.1%	4.6%	1.1%	2.64	3.97	—
2026	17	ROK MLE	DSL Cubs Blue	11	11	31	124	36	15	1	100%	2.8	19.7%	15.1%	4.6%	1.1%	2.64	3.97	—
2026	17	ROK RAW	DSL Cubs Blue	11	11	31	124	36	15	1	100%	2.8	29.0%	12.1%	16.9%	0.8%	2.64	2.64	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	18	MLB	CHC	3	3	18	76	17	10	2	100%	6.0	22.2%	13.5%	8.7%	2.9%	4.93	4.93	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	19	MLB MLE	CHC	5	5	29	122	28	15	4	100%	5.8	22.7%	12.0%	10.7%	2.9%	4.75	4.67	+0.1
2028	19	MLB CTX	CHC	3	3	14	59	13	7	2	100%	4.7	22.7%	12.0%	10.7%	2.9%	4.75	4.67	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		3	3	14	60	14	7	2	100%	4.8	22.7%	12.0%	10.7%	2.9%	4.75	4.29	+0.1
/ 200 IP	—	RAW		46	46	200	844	196	98	28	100%	4.3	22.7%	12.0%	10.7%	2.9%	4.75	4.29	+1.4
Career	—	MLE		11	11	31	124	24	19	1	100%	2.8	19.7%	15.1%	4.6%	1.1%	2.64	3.97	+0.1
/ 200 IP	—	MLE		72	72	200	809	160	122	9	100%	2.8	19.7%	15.1%	4.6%	1.1%	2.64	3.97	+0.5

Career Path Comps

What happened to similar pitchers from this age · Y-axis: ERA+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

			Profile at Match Age					Next 3 Yrs				Career
Comp	Age	Role	FIP	K%	BB%	HR/BF	BABIP	FIP	K%	K-BB%	IP	ΔFIP	Low FIP	IP	Match
Jose Serva (OGILVIE)	—	—	4.93	22.2%	13.5%	2.9%	—	4.67	22.7%	10.7%	29	-0.26	—	—	—
Jagger Haynes L 2023 · 4.25 FIP	20	SP	4.25	19.7%	13.0%	2.1%	.303	4.98	17.7%	3.9%	349	+0.73	4.25	374	86
Julio Mendez L 2022 · 3.83 FIP	17	SP	3.83	23.8%	15.8%	1.3%	.302	4.61	16.3%	3.1%	155	+0.78	3.83	290	85
Ethan Lindow L 2017 · 4.33 FIP	18	SP	4.33	19.1%	12.4%	2.3%	.329	2.95	19.8%	14.0%	111	-1.38	2.95	435	84
Robinson Ortiz L 2018 · 3.85 FIP	18	SP-	3.85	21.0%	11.0%	2.1%	.312	5.36	15.2%	0.6%	98	+1.51	2.29	276	82
Jordan Woods L 2024 · 4.51 FIP	20	SP	4.51	20.5%	10.3%	3.3%	.329	4.18	20.5%	8.3%	139	-0.33	3.92	170	82
Jeremy Gonzalez L 2023 · 4.02 FIP	18	SP	4.02	19.6%	10.6%	2.2%	.290	4.53	14.4%	-1.1%	83	+0.51	3.39	148	81
Brady Aiken L 2016 · 3.79 FIP	19	SP	3.79	20.0%	13.7%	1.2%	.443	5.96	11.0%	-8.9%	132	+2.17	3.79	156	77
Jacob Bresnahan L 2024 · 4.95 FIP	19	SP	4.95	20.2%	14.1%	3.2%	.292	3.92	23.2%	11.1%	208	-1.03	3.03	277	77
Jackson Humphries L 2023 · 4.48 FIP	19	SP	4.48	19.8%	14.0%	2.3%	.302	5.94	20.8%	1.5%	248	+1.46	4.48	305	76
Jay Groome L 2017 · 4.56 FIP	18	SP	4.56	21.6%	14.8%	2.6%	.345	—	—	—	—	—	4.46	420	75
Deyer Zapata L 2022 · 4.25 FIP	18	SP	4.25	18.8%	14.3%	1.7%	.309	5.18	17.5%	4.0%	50	+0.93	3.77	130	75
Ryan Rolison L 2018 · 3.88 FIP	21	SP	3.88	21.2%	9.2%	2.6%	.200	4.41	19.1%	11.5%	191	+0.53	3.81	390	74
Roberto Medina L 2023 · 4.85 FIP	18	SP	4.85	21.6%	21.7%	1.5%	.313	5.67	16.4%	-2.1%	73	+0.82	3.87	109	74
Liam Sullivan L 2023 · 5.78 FIP	21	SP	5.78	25.7%	20.5%	4.1%	.290	5.79	20.9%	7.2%	141	+0.01	4.45	156	73
Jesus Gomez L 2019 · 5.12 FIP	18	SP	5.12	19.3%	12.4%	3.8%	.275	4.40	24.3%	9.8%	23	-0.72	4.22	121	73
Luke Little L 2021 · 4.02 FIP	20	SP-	4.02	25.8%	12.5%	2.8%	.200	2.91	28.0%	12.3%	155	-1.11	2.74	277	73
Miguel Flores L 2024 · 4.30 FIP	19	SP	4.30	21.2%	16.5%	1.6%	.294	4.90	17.4%	-0.3%	127	+0.60	4.30	173	72
Blake Townsend L 2021 · 3.78 FIP	20	SP-	3.78	26.7%	11.2%	2.8%	.286	4.01	18.5%	4.8%	96	+0.23	3.34	305	72
Reinold Navarro L 2024 · 4.92 FIP	17	SP	4.92	21.7%	22.6%	1.4%	.211	4.32	29.4%	5.7%	95	-0.60	3.55	119	72
Kris Bubic L 2018 · 3.97 FIP	20	SP	3.97	21.0%	13.8%	1.6%	.367	3.99	22.5%	13.0%	329	+0.02	2.13	755	71